It is important to understand the risks, challenges, and adverse effects on Sustainable development goals (SDGs) associated with the accelerated growth of AI. New green initiatives are also evolving to mitigate these challenges. Therefore, it is imperative to analyse the relationship dynamics between the risks involved, their mitigating initiatives, and the SDGs.
This study employed an extensive literature review, discussions with experts, and an examination of causality loops in AI challenges to achieve the SDGs. The stepwise weight assessment ratio analysis (SWARA) was deployed to identify the key challenges, and the analytic hierarchy process (AHP)facilitated an understanding of the relationships between AI challenges and mitigating initiatives.
The final synthesised outcome from AHP has prioritized the seven challenges from accelerated AI growth. The top three challenges – human inequality and biases, the increased digital divide, and unsustainable energy consumption constitute 79% of the impact of the challenges to the growing AI applications.
The prioritised factors identified will serve stakeholders in developing relevant policies, investing in the right areas, and facilitating where to focus in the sustainability journey. AHP results have prompted the need for an index-the SDG Achievement Index (SAI). The index is expected to find application in real business.
The application of the AHP methodology to analyse the hierarchy and priorities in AI challenges and green initiatives is the original contribution of this research study. The suggested measure, SAI, is a useful approach for quantifying and tracking the trends of the impact of Green AI initiatives on the SDGs. The current research study is topical, enriching the literature, and insightful to practitioners.
